Latent resonators are versatile constraints on dynamics which could be applied to a wide range of prosaic models. As opposed to models trained via gradient descent, those constructs are closed-form — they can be computed in sublinear time with respect to dataset size, and therefore can be obtained cheaply and quickly. By making use of the their associated Boolean logic in clever ways, we might be able to use them as safeguards against deceptive behavior and inner alignment more broadly by applying them directly to latent activations.